Proteome‐wide profiling reveals dysregulated molecular features and accelerated aging in osteoporosis: A 9.8‐year prospective study

Author:

Xu Jinjian1ORCID,Cai Xue23,Miao Zelei23,Yan Yan1,Chen Danyu1,Yang Zhen‐xiao1,Yue Liang23,Hu Wei1,Zhuo Laibao1,Wang Jia‐ting1,Xue Zhangzhi23,Fu Yuanqing23ORCID,Xu Ying4,Zheng Ju‐Sheng23ORCID,Guo Tiannan23ORCID,Chen Yu‐ming1ORCID

Affiliation:

1. Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health Sun Yat‐sen University Guangzhou China

2. School of Life Sciences Westlake University Hangzhou China

3. Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine Hangzhou China

4. Shenzhen Bao'an Center for Chronic Diseases Control Shenzhen China

Abstract

AbstractThe role of circulatory proteomics in osteoporosis is unclear. Proteome‐wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography–tandem mass spectrometry (LC–MS/MS) at baseline, and the 2nd, and 3rd follow‐ups (7704 person‐tests) in the prospective Chinese cohorts with 9.8 follow‐up years: discovery cohort (n = 1785) and internal validation cohort (n = 1630). Bone mineral density (BMD) was measured using dual‐energy X‐ray absorptiometry (DXA) at follow‐ups 1 through 3 at lumbar spine (LS) and femoral neck (FN). We used the Light Gradient Boosting Machine (LightGBM) to identify the osteoporosis (OP)‐related proteomic features. The relationships between serum proteins and BMD in the two cohorts were estimated by linear mixed‐effects model (LMM). Meta‐analysis was then performed to explore the combined associations. We identified 53 proteins associated with osteoporosis using LightGBM, and a meta‐analysis showed that 22 of these proteins illuminated a significant correlation with BMD (p < 0.05). The most common proteins among them were PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, and THBG. The identified proteins were used to generate the biological age (BA) of bone. Each 1 SD‐year increase in KDM‐Proage was associated with higher risk of LS‐OP (hazard ratio [HR], 1.25; 95% CI, 1.14–1.36, p = 4.96 × 10−06), and FN‐OP (HR, 1.13; 95% CI, 1.02–1.23, p = 9.71 × 10−03). The findings uncovered that the apolipoproteins, zymoproteins, complements, and binding proteins presented new mechanistic insights into osteoporosis. Serum proteomics could be a crucial indicator for evaluating bone aging.

Funder

National Natural Science Foundation of China

Shenzhen Fundamental Research Program

Publisher

Wiley

Subject

Cell Biology,Aging

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